forked from M-Labs/nalgebra
108 lines
3.2 KiB
Rust
108 lines
3.2 KiB
Rust
use std::cmp;
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use nl::LU;
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use na::{DMatrix, DVector, Matrix3x4, Matrix4, Matrix4x3, Vector4};
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quickcheck!{
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fn lup(m: DMatrix<f64>) -> bool {
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if m.len() != 0 {
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let lup = LU::new(m.clone());
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let l = lup.l();
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let u = lup.u();
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let mut computed1 = &l * &u;
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lup.permute(&mut computed1);
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let computed2 = lup.p() * l * u;
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relative_eq!(computed1, m, epsilon = 1.0e-7) &&
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relative_eq!(computed2, m, epsilon = 1.0e-7)
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}
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else {
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true
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}
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}
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fn lu_static(m: Matrix3x4<f64>) -> bool {
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let lup = LU::new(m);
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let l = lup.l();
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let u = lup.u();
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let mut computed1 = l * u;
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lup.permute(&mut computed1);
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let computed2 = lup.p() * l * u;
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relative_eq!(computed1, m, epsilon = 1.0e-7) &&
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relative_eq!(computed2, m, epsilon = 1.0e-7)
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}
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fn lu_solve(n: usize, nb: usize) -> bool {
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if n != 0 {
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let n = cmp::min(n, 25); // To avoid slowing down the test too much.
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let nb = cmp::min(nb, 25); // To avoid slowing down the test too much.
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let m = DMatrix::<f64>::new_random(n, n);
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let lup = LU::new(m.clone());
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let b1 = DVector::new_random(n);
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let b2 = DMatrix::new_random(n, nb);
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let sol1 = lup.solve(&b1).unwrap();
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let sol2 = lup.solve(&b2).unwrap();
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let tr_sol1 = lup.solve_transpose(&b1).unwrap();
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let tr_sol2 = lup.solve_transpose(&b2).unwrap();
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relative_eq!(&m * sol1, b1, epsilon = 1.0e-7) &&
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relative_eq!(&m * sol2, b2, epsilon = 1.0e-7) &&
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relative_eq!(m.transpose() * tr_sol1, b1, epsilon = 1.0e-7) &&
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relative_eq!(m.transpose() * tr_sol2, b2, epsilon = 1.0e-7)
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}
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else {
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true
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}
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}
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fn lu_solve_static(m: Matrix4<f64>) -> bool {
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let lup = LU::new(m);
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let b1 = Vector4::new_random();
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let b2 = Matrix4x3::new_random();
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let sol1 = lup.solve(&b1).unwrap();
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let sol2 = lup.solve(&b2).unwrap();
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let tr_sol1 = lup.solve_transpose(&b1).unwrap();
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let tr_sol2 = lup.solve_transpose(&b2).unwrap();
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relative_eq!(m * sol1, b1, epsilon = 1.0e-7) &&
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relative_eq!(m * sol2, b2, epsilon = 1.0e-7) &&
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relative_eq!(m.transpose() * tr_sol1, b1, epsilon = 1.0e-7) &&
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relative_eq!(m.transpose() * tr_sol2, b2, epsilon = 1.0e-7)
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}
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fn lu_inverse(n: usize) -> bool {
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if n != 0 {
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let n = cmp::min(n, 25); // To avoid slowing down the test too much.
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let m = DMatrix::<f64>::new_random(n, n);
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if let Some(m1) = LU::new(m.clone()).inverse() {
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let id1 = &m * &m1;
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let id2 = &m1 * &m;
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return id1.is_identity(1.0e-7) && id2.is_identity(1.0e-7);
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}
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}
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return true;
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}
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fn lu_inverse_static(m: Matrix4<f64>) -> bool {
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match LU::new(m.clone()).inverse() {
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Some(m1) => {
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let id1 = &m * &m1;
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let id2 = &m1 * &m;
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id1.is_identity(1.0e-5) && id2.is_identity(1.0e-5)
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},
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None => true
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}
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}
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}
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